One Health as a scientific and policy-driven approach reflects the urgent need to tackle complex health challenges that transcend traditional disciplinary boundaries. Research rooted in this paradigm addresses zoonotic diseases, antimicrobial resistance, environmental contamination, and ecosystem disruptions—each entwined in a delicate balance affecting global health security. The recent surge in publications marks a growing recognition of One Health’s indispensable role, with Europe, Asia, and Africa emerging as hotspots for research production. Despite this geographic diversification, the leadership and strategic decision-making within One Health research remain heavily skewed towards institutions based in economically advanced nations.

The foundational framework guiding One Health implementation on a global scale is the Joint Plan of Action (JPA) 2022–2026 developed by the One Health Quadripartite, comprised of the Food and Agriculture Organization (FAO), the United Nations Environment Programme (UNEP), the World Health Organization (WHO), and the World Organisation for Animal Health (WOAH). The JPA delineates six critical action tracks designed to drive coordinated global efforts addressing surveillance, risk communication, capacity building, and sustainable health system strengthening. This bibliometric study uniquely maps scholarly outputs against these JPA priorities, providing a lens to assess alignment between research activities and policy-driven goals.

As detailed in the analysis, One Health research has broadened its thematic scope far beyond the initial focus on zoonoses, encompassing vector-borne diseases, antimicrobial resistance, and interdisciplinary discussions on animal and environmental health. The diversification underscores a maturation in the field and a growing appreciation for the multifaceted determinants of health that include microbial ecology, agricultural practices, and environmental exposures. Nevertheless, it is striking to note that certain critical areas such as the health impacts of pesticides and mycotoxins on food safety, as well as the effects of biodiversity loss and land-use change on ecosystem integrity and zoonotic spillovers, are comparatively under-researched, lagging by orders of magnitude behind more conventional topics.

Despite the presence of numerous collaborative ventures and multinational networks, this study reveals entrenched power imbalances in global One Health research dynamics. Most research concerning Africa and Asia—which bear a disproportionate burden of emerging infectious diseases and environmental health challenges—is predominantly led and published by institutions based in Europe and North America. This disparity raises profound concerns about agenda-setting, representation, and the equitable distribution of research resources and intellectual leadership. Institutes in high-income countries (HICs) dominate publication outputs and consequently shape the research priorities and narratives, often sidelining nuanced regional needs in low- and middle-income countries (LMICs).

The consequences of this asymmetry are far-reaching. When LMIC researchers have a limited role in defining research priorities or leading projects, the outcomes might lack culturally relevant insights or fail to address locally pressing problems adequately. This top-down dynamic risks undermining local engagement, trust, and the effective translation of research into policy and practice. Dr. Dannie Romney, project director of CABI’s One Health Hub and a key author of the study, underscores that without equitable collaboration, the global One Health agenda risks perpetuating scientific colonialism, with research initiatives misaligned from the ground realities they intend to serve.

Empowering researchers in LMICs to dictate research directions and participate fully in knowledge production is essential for fostering ownership and buy-in. The study argues that building sustainable research capacity in these regions would enhance their ability to bridge the gap between empirical evidence and health policy formulation. This strategic capacity building includes infrastructural investments, training opportunities, mentorship programs, and equitable funding mechanisms designed to support local leadership. Such efforts could ultimately catalyze a paradigm shift towards genuinely inclusive and context-sensitive One Health research.

The implications of rebalancing power within the One Health research ecosystem extend beyond academia. Enhanced local leadership in research can contribute profoundly to global health equity by facilitating policies calibrated to the socio-ecological realities of diverse populations. Moreover, fostering local expertise is likely to improve surveillance and rapid response capabilities for emerging infectious threats, thereby reinforcing global health security. Policymakers and international agencies must heed these findings and collaborate to mitigate disparities that hamper a truly integrated One Health strategy.

CABI’s One Health Hub conducted the bibliometric analysis using advanced methodologies, including topic modeling, to categorize and evaluate the body of literature in relation to the JPA’s six action tracks and various scientific disciplines. This robust approach allows for objective identification of research trends, emerging topics, and gaps in the existing knowledge landscape. The combined use of quantitative bibliometrics and qualitative thematic mapping delivers a nuanced understanding that can guide strategic funding priorities, foster new interdisciplinary networks, and encourage collaborations more reflective of global diversity.

The study is complemented by two comprehensive evidence briefs that synthesize key findings: one tracking the evolution of One Health research and the other advocating for elevating the voice of the Global South in global health dialogues. These documents serve as invaluable resources for researchers, practitioners, and funders committed to transforming One Health from conceptual promise into effective, equitable action. Additionally, upcoming webinars hosted by CABI in partnership with FAO’s One Health Knowledge Nexus aim to disseminate these insights widely and foster conversations around future research priorities and equity considerations.

Ultimately, this landmark analysis signals a critical moment for the One Health community. The exponential growth in research outputs signals enthusiasm and recognition of the approach’s relevance, but also illuminates systemic flaws that risk entrenching inequalities. Addressing these challenges demands concerted and sustained action across sectors, funding bodies, and countries. Bridging the divide between LMICs and HICs in research leadership will not only democratize scientific discourse but also enhance the feasibility and effectiveness of One Health solutions in addressing the complex health challenges of the 21st century.

As the global health landscape becomes increasingly interconnected and vulnerable to emerging threats such as zoonotic spillovers, antimicrobial resistance, and environmental degradation, fostering an inclusive One Health research ecosystem is imperative. The findings from CABI’s comprehensive bibliometric study offer both a roadmap and a call to action to ensure that the future of One Health research transcends geopolitical boundaries and reflects a truly global partnership dedicated to safeguarding health at every interface.

Subject of Research: Not applicable

Article Title: A bibliometric analysis of One Health research, guided by the Joint Plan of Action, 2010–2024

News Publication Date: 22-Oct-2025

Web References:

• One Health Quadripartite Joint Plan of Action 2022–2026: https://www.fao.org/one-health/resources/publications/joint-plan-of-action
• CABI One Health Hub: https://www.cabi.org/one-health-hub/
• One Health Knowledge Bank: https://www.cabidigitallibrary.org/product/1k

References:
Szomszor M., Kadzamira M.A.T.J., Ishii-Adajar H., Leyland T., Schaffner U., Häsler B., Wright B., Danielsen S., Romney D. A bibliometric analysis of One Health research, guided by the Joint Plan of Action, 2010–2024. CABI One Health. 4:1, 0032 (2025). DOI: 10.1079/cabionehealth.2025.0032

Image Credits: CABI

Keywords: Agriculture

Central to the workshop’s agenda was the concept of the exposome itself, a term that encapsulates all the environmental exposures an individual encounters from conception onward. Unlike genetic factors, which have been extensively mapped and studied over recent decades, the exposome remains an elusive frontier, owing to its vast scope and dynamic nature. Participants grappled with the challenge of translating this complexity into quantifiable measures that can be standardized across diverse research fields. The discussion illuminated the pressing need for novel frameworks capable of integrating multifaceted data streams, ranging from chemical exposures to psychosocial stressors.

A critical insight from the workshop was the recognition that traditional siloed approaches fall short when addressing the exposome’s multifactorial characteristics. Scientists emphasized that bridging disciplinary divides is not only advantageous but essential. For instance, epidemiologists bring expertise in population-level data analysis, yet they rely heavily on accurate and granular exposure information, often generated by environmental scientists and biologists. By fostering robust collaboration, the Coordinating Center aims to create interoperable data infrastructures and analytic tools that can handle heterogeneous data while maintaining reproducibility and reliability across studies.

Technological innovation emerged as a cornerstone of these efforts. With advances in high-throughput omics technologies and wearable sensors, the capacity to monitor individual exposures in real time has increased exponentially. The workshop spotlighted these innovations, discussing how integrating molecular profiling—such as metabolomics and epigenomics—with external exposure measurements can elucidate biological pathways that mediate the impact of the exposome on aging. This multilayered approach promises to move beyond association studies toward mechanistic insights, unraveling how environmental factors trigger cellular changes that culminate in age-related pathologies.

The workshop delved deeply into data harmonization challenges, recognizing that disparate measurement scales, temporal resolutions, and exposure types complicate efforts to build unified exposome assessments. To address this, participants advocated for developing shared ontologies and data standards that transcend specific studies and enable seamless data integration. Machine learning and artificial intelligence algorithms were highlighted as powerful tools for extracting meaningful patterns from complex and voluminous datasets. However, the importance of transparency and interpretability in these computational models was emphasized to ensure that their outputs are biologically and clinically meaningful.

A particularly novel aspect of the Coordinating Center’s vision is the incorporation of socio-environmental contexts into exposome research. Aging is not solely a biological process but is heavily influenced by social determinants of health, including socioeconomic status, education, and neighborhood characteristics. Workshop discussions underscored the necessity of embedding these variables into exposome frameworks, thus moving toward a holistic view that recognizes the interplay between environment, biology, and society. This integrative perspective is poised to enhance our understanding of health disparities and guide targeted interventions.

Another dimension explored was the ethical and privacy considerations inherent in exposome research. Collecting detailed environmental and biological data presents significant challenges related to consent, data ownership, and potential misuse. The workshop underscored the requirement for establishing robust governance frameworks that protect participant rights while facilitating scientific discovery. Moreover, community engagement emerged as a vital strategy to foster trust and ensure that research agendas align with the needs and values of diverse populations.

Methodologically, the Coordinating Center champions the development of dynamic, longitudinal study designs. Aging is a gradual and nonlinear process, and capturing the temporal evolution of exposures and their biological effects demands repeated assessments over extended periods. The workshop highlighted how innovations in remote sensing and biosampling technologies enable such longitudinal tracking with minimal participant burden. By aligning temporal data across exposures and biological responses, researchers can better infer causality and identify critical windows of susceptibility during the aging process.

Central to implementing these ambitious goals is capacity building and training of a new generation of interdisciplinary scientists. The workshop acknowledged current gaps in workforce expertise and called for curriculum reforms that integrate quantitative, biological, and social sciences. The creation of cross-disciplinary training programs, fellowships, and collaborative research hubs was proposed to nurture professionals adept at navigating the exposome landscape. Empowering researchers with these skills is critical to sustaining the momentum generated by the Coordinating Center.

The workshop also emphasized the translational potential of exposome research. By generating refined exposure metrics and linking them with biological markers of aging, scientists can inform personalized medicine approaches and public health strategies. For example, identifying environmental triggers of chronic diseases common in older adults can lead to targeted prevention interventions. Furthermore, these insights have implications for policy-making, environmental regulation, and urban planning, thereby extending their impact beyond individual health to societal well-being.

Underpinning these discussions was the recognition that interoperability extends beyond data to include harmonized terminology and conceptual frameworks. The Coordinating Center advocates for the establishment of consensus vocabularies and definitions to facilitate cross-study comparisons and meta-analyses. This endeavor requires global collaboration, including engagement with international exposome initiatives, to ensure that findings are generalizable and applicable across diverse populations and environments. The workshop served as a critical node in fostering these connections.

Importantly, the Coordinating Center workshop acknowledged the ongoing challenges and limitations inherent in exposome research. The vast heterogeneity of exposures, potential confounding factors, and the dynamic interplay between genetics and environment create complex analytical hurdles. To overcome these, the workshop called for iterative refinement of models and validation through experimental systems, such as organoids and animal models, that can dissect causative mechanisms. This integrative strategy bridges observational and experimental methodologies.

Finally, the workshop concluded with a vision for a future where exposome science transforms aging research. Achieving this vision requires sustained investment, collaborative spirit, and innovative thinking. The participants conveyed a shared commitment to building infrastructure, developing shared resources, and fostering open science principles to accelerate discovery. This concerted effort is poised to unlock new paradigms in our understanding of aging, ultimately improving healthspan and quality of life for diverse populations around the globe.

The Gateway Exposome Coordinating Center workshop, as documented by Lee and colleagues, thus represents a milestone in the quest to unify disparate scientific approaches into a cohesive exposome research ecosystem. By confronting the technical, methodological, and ethical complexities inherent in this endeavor, it sets the stage for transformative advances that promise to redefine aging biology and environmental health sciences in the decades to come.

Subject of Research:
Integrative exposome research to understand environmental influences on aging through interdisciplinary collaboration and advanced methodological frameworks.

Article Title:
Insights into bridging disciplines and building measures from the Gateway Exposome Coordinating Center workshop.

Article References:

Lee, J., Bindas, A., Knapp, D. et al. Insights into bridging disciplines and building measures from the Gateway Exposome Coordinating Center workshop. Nat Aging (2025). https://doi.org/10.1038/s43587-025-00923-0

Image Credits: AI Generated

BEACON is the product of a strategic partnership primarily housed within Boston University’s Center on Emerging Infectious Diseases (CEID). This center’s long-standing expertise in global health security and emerging pathogen research provides the scientific foundation for BEACON’s operational framework. Complementing CEID’s strengths are collaborations with the Hariri Institute for Computing and Data Sciences, renowned for their advancements in computational methodologies, and HealthMap, a pioneer in real-time infectious disease outbreak monitoring based at Boston Children’s Hospital. This alliance leverages institutional excellence across diverse domains, fostering a robust infrastructure capable of tackling complex biothreat challenges.

At the heart of BEACON’s functionality lies the integration of proprietary AI tools, most notably the PandemIQ Llama large language model. This LLM has been meticulously adapted and trained to optimize performance specifically for outbreak data analysis and report generation. Unlike generic language models, PandemIQ Llama exhibits domain-specific acumen, enabling it to parse epidemiological reports, synthesize disparate data streams, and deliver nuanced contextualization of emerging threats. This generative AI-based architecture allows BEACON to process sentinel case reports and epidemiological alerts in near real-time, dramatically shortening the lag between threat detection and public health response.

The conceptual design of BEACON draws parallels to early-warning systems used in environmental monitoring, such as those for hurricanes or wildfires. Similarly, BEACON’s objective is to serve as a sentinel for biological hazards, offering timely alerts that highlight clusters, outbreaks, or anomalous health events before they proliferate. Through transparent data sharing and rapid contextual analysis, it empowers public health authorities, clinicians, researchers, and the general public to act proactively. This democratization of information contrasts with traditional surveillance systems that often operate within institutional silos and report with significant delays.

BEACON’s open-source nature distinguishes it as the first global surveillance platform to be freely accessible, encouraging continuous interaction from a broad community of stakeholders. The platform’s interface provides not only raw data but enriched reports that elucidate why a given biological threat warrants concern and help prioritize response efforts accordingly. This level of integration fosters an ecosystem where data generation, expert interpretation, and policy-making are seamlessly connected, bolstering preparedness and resilience at local, national, and global scales.

The innovative use of generative AI in epidemiological surveillance embodied by BEACON represents a major leap forward. Traditional public health monitoring systems rely heavily on manual data curation and retrospective analyses, which can impede timely interventions. BEACON’s AI-driven approach facilitates autonomous extraction and summarization of critical outbreak information from multifarious sources, including media reports, social networks, and scientific literature. This augmentation of human expertise with machine intelligence accelerates situational awareness and mitigates the risks of unnoticed threat escalation.

Backing the technical prowess of BEACON is substantial financial and institutional support. With over six million dollars in funding from notable organizations such as the National Science Foundation and the Gates Foundation, alongside Boston University’s investments, BEACON enjoys a strong sustainability foundation. Institutional partnerships extend to prestigious global health entities including the World Health Organization’s Epidemic Intelligence from Open Sources (EIOS) initiative, the World Organisation for Animal Health, and the Coalition for Epidemic Preparedness Innovations. These alliances enhance BEACON’s data streams, validation protocols, and dissemination networks, ensuring comprehensive surveillance coverage.

Beyond financial backing, BEACON’s integration with state and federal public health agencies, including the Centers for Disease Control and Prevention’s Center for Forecasting and Outbreak Analytics, exemplifies its role as a nexus for coordinated response efforts. Such collaborations underscore the platform’s utility as a decision support tool, guiding resource allocation, outbreak investigation, and policy formulation. The capacity to cross-validate data with official epidemiologic intelligence significantly elevates trustworthiness and actionable accuracy.

The platform prototype is currently live at beaconbio.org, enabling a diverse user base to explore its functionalities. This live testing phase invites feedback from clinicians, epidemiologists, policy makers, and even informed members of the general public, enriching the platform’s evolution through iterative refinement. The open solicitation of input exemplifies BEACON’s commitment to inclusivity and transparency, crucial attributes in garnering widespread acceptance and utility of a public health tool.

Scheduled for official launch on April 24, 2025, the BEACON inaugural event will be accessible both in Boston and virtually via Zoom, fostering broad engagement. The event aims to spotlight the platform’s technical intricacies, real-world applications, and visions for future enhancements. By opening the doors to the public and scientific community alike, BEACON positions itself as a collaborative venture inviting collective stewardship over global biological threat surveillance.

In aligning its mission with principles of accessibility and equity, BEACON’s framework ensures that low-resource regions and underserved populations can benefit from timely access to critical biothreat intelligence. This emphasis on global availability without financial barriers addresses key limitations encountered in prior platforms that restricted data access due to proprietary technologies or subscription costs. As emerging diseases often manifest first in resource-limited settings, such inclusivity is pivotal for meaningful early-warning systems.

Looking ahead, BEACON’s fusion of AI, LLMs, and multidisciplinary expert networks exemplifies the future of infectious disease monitoring. The platform’s ability to dynamically synthesize heterogeneous data with contextual awareness promises not only improved outbreak detection but also valuable insights into pathogen evolution, transmission dynamics, and the socio-environmental factors influencing disease emergence. These insights hold profound implications for research, policy, and public health interventions aimed at minimizing epidemic and pandemic impacts.

In summary, the inauguration of BEACON marks a watershed moment in global health intelligence infrastructure. By harnessing the power of sophisticated generative AI tailored for epidemiology and embedding that within a collaborative platform backed by leading institutions, BEACON sets a new standard for biothreat surveillance. This initiative offers a scalable, transparent, and accessible solution that could redefine how the world anticipates and responds to infectious disease threats in an increasingly interconnected and complex biosphere.

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Subject of Research: Emerging infectious disease surveillance using artificial intelligence and large language models

Article Title: [Not provided in the source]

News Publication Date: [Not explicitly stated, but event date is April 24, 2025]

Web References:
– https://www.bu.edu/ceid/
– https://www.bu.edu/hic/
– https://www.healthmap.org/en/
– https://www.childrenshospital.org/
– http://beaconbio.org
– https://www.bu.edu/articles/2025/open-source-ai-infectious-diseases-monitoring-tool/
– https://www.eventbrite.com/e/advances-in-global-disease-surveillance-an-introduction-to-beacon-tickets-1237688021189?aff=oddtdtcreator

Keywords: Infectious diseases, Public health, Epidemics, Computer science, Artificial intelligence